Analyte detection in physiological samples of tissue or fluids, e.g. blood or blood derived products, is of ever increasing importance to today's society. Analyte detection assays find use in a variety of applications, including clinical laboratory testing, home testing, etc., where the results of such testing play a prominent role in diagnosis and management in a variety of disease conditions. Analytes of interest include alcohol, formaldehyde, glucose, glutamic acid, glycerol, beta-hydroxybutyrate, L-lactate, leucine, malic acid, pyruvic acid, steroids, ascorbic acid, acetone and other ketone bodies, folate, ammonia, bilirubin, creatinine, hemoglobins, lipids, phenylalanine, proteins (including albumin andglobulins), triglycerides, urea, as well as pharmaceuticals and drugs of abuse. As such, analyte testing is of increasing importance to today's society.
While the concentration of blood analytes can be monitored in a variety of different ways, of increasing interest are non-invasive methods of monitoring the concentration of blood analytes. For example, because of its importance in the management of diabetes, much research and effort has gone into the development of non-invasive methods and devices for monitoring the concentration of blood glucose.
One type of non-invasive method for measuring blood glucose involves the use of near infra-red spectroscopy, in which light in the near infra-red wavelength region is passed through or reflected from a sample and the emitted signal is used to derive the concentration of analyte in the sample. A number of non-invasive devices for monitoring blood analytes, including blood glucose, with near infra-red spectroscopy are known to those of skill in the art, including those disclosed in the references listed in the relevant literature section, supra.
In order to measure the absorption of light by a sample in discrete wavelength regions of the near infrared spectrum, a method of separating the wavelength contributions is needed. Such methods described in prior art include filter wheels, diffraction-grating-based spectrometers, acousto-optic tunable filters (AOTF) and Fourier transform infrared (FTIR) spectrometers. If the analyte of interest is strongly light-absorbing and easily distinguishable spectroscopically, a filter wheel apparatus may provide enough discrete wavelengths to allow the analyte concentration to be determined. However, in cases, such as glucose in tissue, where the analyte of interest is a weakly absorbing component in a complex mixture, a large number (greater than 10 and more commonly greater than 100) of discrete wavelength regions must be separately analyzed in order to measure the analyte concentration.
In such cases, a diffraction-grating-based, AOTF, or FTIR spectrometer can be used to resolve the spectrum into multiple wavelength regions. In addition to the wavelength resolution of the measurement technique, an important consideration for highly scattering samples such as tissue and blood, is the optical throughput or flux through the spectrometer. In a diffraction-grating-based spectrometer with a single detector element, the throughput of the spectrometer is inversely proportional to the wavelength resolution. Thus, if a large number of wavelength regions are to be resolved, the amount of light reaching the detector will be small. Arrays of detectors may be used to increase the throughput of the spectrometer, but such arrays with high sensitivity to near infrared wavelengths (1-2.5 μm) tend to be expensive. Further, the calibration and drift of the different detector elements in the array becomes a source of inaccuracy in the analyte determination.
In AOTF spectrometers, the individual wavelength regions are separately measured by tuning the filter. Since the entire spectrum is not simultaneously measured, changes in the sample with respect to time can distort the measured spectrum. Further, the necessity of separately measuring the wavelength regions results in a loss in optical throughput compared to techniques that measure the entire spectrum simultaneously.
FTIR spectrometers offer the advantage of high optical throughput combined with high wavelength resolution with the use of a single detector. As a result, for low transmissivity samples (highly scattering and/or strongly absorbing) containing a complex mixture of analytes, FTIR provides an advantage compared to filter-wheel, AOTF, and grating-based spectrometers. While near infra-red FTIR devices and methods show great promise in the field of non-invasive analyte detection, technical hurdles remain to be overcome if such devices are to become commercially viable products. Such technical hurdles include: problems with instrument drift, the need for ultra high precision analog to digital converters, and the like.
As such, there is a continued interest in the development of new devices and methods for near infra-red based analyte concentration detection.
Relevant Literature
Dual Beam Fourier Transform Infrared (DB-FTIR) spectroscopy is described in U.S. Pat. No. 4,999,010, as well as in: Beduhn & White, Applied Spectroscopy (1986) 40: 628-632; Kuehl & Griffiths, Anal. Chem. (March. 1978) 50:418-422 and P. R. Griffiths and J. A. de Haseth, FOURIER TRANSFORM INFRARED SPECTROSCOPY, Chemical Analysis, Vol. 83(1986) John Wiley and Sons, New York, pp 298-311. See also FTIR: FOURIER TRANSFORM INFRARED: A CONSTANTLY EVOLVING TECHNOLOGY, Sean Johnston, Ellis Horwood, N.Y., (1991), pp. 260-274]. Infrared spectroscopy based non-invasive blood analyte detection protocols are described in U.S. Pat. Nos.: 6,016,435; 6,002,953; 5,957,841; 5,945,676; 5,830,132; 5,574,283; 5,424,545; 5,237,178; 5,222,496; 5,204,532; and 4,882,492; the disclosures of which are herein incorporated by reference; as well as Klonoff, “Noninvasive blood glucose monitoring,” Diabetes Care (March, 1997)20(3):433-7.